Network bricolage of international entrepreneurs for new market entry: a cross-national study of small biotech firms
Bibliographic record
Abstract
Purpose The authors aimed to contribute to the interface of comparative international entrepreneurship and international marketing by exploring the micro-foundations and micro-processes of network bricolage aimed at international market entry among the entrepreneurs of small biotechnology firms. The research questions of the study are (1) How do the international entrepreneurs of small firms act and use their domestic and/or international networks for new market entry? (2) How are the micro-foundations and micro-processes of networking similar or different between individuals from different countries? Design/methodology/approach A qualitative research design was used to investigate six cases from different countries of origin, looking at the micro-foundations and micro-processes underlying international market entry undertaken by entrepreneurs from Canada, Finland and New Zealand. Findings The micro-foundations for network bricolage by international entrepreneurs were taken to involve features of the country of origin, including market size and location, and the usefulness of the official language of the nation. The micro-processes were taken to involve the international entrepreneur’s network bricolage actions (i.e. collaborating and generating, obtaining and applying, reaching and maintaining, and seeking and reviewing), while encompassing also the location of their networks (domestic and/or international) and the operational domains these belonged to (R&D, funding, sales channel and customer). The study categorised three types of international entrepreneurs undertaking new market entry, illustrating cross-national differences: (1) sales-channel-oriented seekers, (2) funding-oriented riders and (3) customer-oriented hunters. Originality/value The study contributes to research on comparative international entrepreneurship and international marketing. This findings show that national-level micro-foundations influence the actions of network bricolage, the importance of various operational domains and the location of the network ties used. This main contribution is a conceptual model based on our cross-national investigation of international entrepreneurs’ networking actions. The authors reveal the micro-foundations and micro-processes relevant to international entrepreneurs’ network bricolage for new market entry, and present examples of international entrepreneur types emerging from our cross-national setting.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".